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Applied Parallel Computing

State of the Art in Scientific Computing

  • Conference proceedings
  • © 2006

Overview

Editors:
  1. Jack Dongarra

    1. Computer Science Department, University of Tennessee, Knoxville, USA

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  2. Kaj Madsen

    1. Department of Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark

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    You can also search for this editor in PubMed   Google Scholar

  3. Jerzy Waśniewski

    1. Informatics & Mathematical Modeling, Technical University of Denmark, Lyngby, Denmark

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: Lecture Notes in Computer Science (LNCS, volume 3732)

Part of the book sub series: Theoretical Computer Science and General Issues (LNTCS)

Included in the following conference series:

Conference proceedings info: PARA 2004.

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Table of contents (139 papers)

  1. Minisymposia

    1. Interval Methods

      1. The Distributed Interval Geometric Machine Model
        • Renata H. S. Reiser, Antônio C. R. Costa, Graçaliz P. Dimuro
        Pages 179-188
      2. New Algorithms for Statistical Analysis of Interval Data
        • Gang Xiang, Scott A. Starks, Vladik Kreinovich, Luc Longpré
        Pages 189-196
      3. On Efficiency of Tightening Bounds in Interval Global Optimization
        • Antanas Žilinskas, Julius Žilinskas
        Pages 197-205

    2. Trends in Large Scale Computing

      1. Trends in Large Scale Computing: An Introduction
        • Scott B. Baden
        Pages 206-206
      2. Ygdrasil: Aggregator Network Toolkit for Large Scale Systems and the Grid
        • Susanne M. Balle, John Bishop, David LaFrance-Linden, Howard Rifkin
        Pages 207-216
      3. Enabling Coupled Scientific Simulations on the Grid
        • Alan Sussman, Henrique Andrade
        Pages 217-224

    3. High Performance Linear Algebra Algoritms

      1. High Performance Linear Algebra Algorithms: An Introduction
        • Fred G. Gustavson, Jerzy Waśniewski
        Pages 225-227
      2. Applying Software Testing Metrics to Lapack
        • David J. Barnes, Tim R. Hopkins
        Pages 228-236
      3. A Matrix-Type for Performance–Portability
        • N. Peter Drakenberg
        Pages 237-246
      4. A New Array Format for Symmetric and Triangular Matrices
        • John A. Gunnels, Fred G. Gustavson
        Pages 247-255
      5. A Family of High-Performance Matrix Multiplication Algorithms
        • John A. Gunnels, Fred G. Gustavson, Greg M. Henry, Robert A. van de Geijn
        Pages 256-265

    4. Substructuring, Dimension Reduction and Applications

      1. Substructuring, Dimension Reduction and Applications: An Introduction
        • Zhaojun Bai, Ren-Cang Li
        Pages 266-266
      2. Parallel Algorithms for Balanced Truncation Model Reduction of Sparse Systems
        • José M. Badía, Peter Benner, Rafael Mayo, Enrique S. Quintana-Ortí
        Pages 267-275
      3. Towards an Optimal Substructuring Method for Model Reduction
        • Zhaojun Bai, Ben-Shan Liao
        Pages 276-285
      4. Model Reduction for RF MEMS Simulation
        • David S. Bindel, Zhaojun Bai, James W. Demmel
        Pages 286-295
      5. A Model-Order Reduction Technique for Low Rank Rational Perturbations of Linear Eigenproblems
        • Frank Blömeling, Heinrich Voss
        Pages 296-304
      6. Parallel Global Optimization of Foundation Schemes in Civil Engineering
        • Raimondas Čiegis, Milda Baravykaitė, Rimantas Belevičius
        Pages 305-312
      7. A Combined Linear and Nonlinear Preconditioning Technique for Incompressible Navier-Stokes Equations
        • Feng-Nan Hwang, Xiao-Chuan Cai
        Pages 313-322
      8. Structure-Preserving Model Reduction
        • Ren-Cang Li, Zhaojun Bai
        Pages 323-332
      9. A Comparison of Parallel Preconditioners for the Sparse Generalized Eigenvalue Problems by Rayleigh-Quotient Minimization
        • Sangback Ma, Ho-Jong Jang
        Pages 333-341
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  1. Applied Parallel Computing. State of the Art in Scientific Computing

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About this book

Introduction The PARA workshops in the past were devoted to parallel computing methods in science and technology. There have been seven PARA meetings to date: PARA’94, PARA’95 and PARA’96 in Lyngby, Denmark, PARA’98 in Umea, ? Sweden, PARA 2000 in Bergen, N- way, PARA 2002 in Espoo, Finland, and PARA 2004 again in Lyngby, Denmark. The ?rst six meetings featured lectures in modern numerical algorithms, computer science, en- neering, and industrial applications, all in the context of scienti?c parallel computing. This meeting in the series, the PARA 2004 Workshop with the title “State of the Art in Scienti?c Computing”, was held in Lyngby, Denmark, June 20–23, 2004. The PARA 2004 Workshop was organized by Jack Dongarra from the University of Tennessee and Oak Ridge National Laboratory, and Kaj Madsen and Jerzy Was ´niewski from the Technical University of Denmark. The emphasis here was shifted to high-performance computing (HPC). The ongoing development of ever more advanced computers provides the potential for solving increasingly dif?cult computational problems. However, given the complexity of modern computer architectures, the task of realizing this potential needs careful attention. For example, the failure to exploit a computer’s memory hi- archy can degrade performance badly. A main concern of HPC is the development of software that optimizes the performance of a given computer. The high cost of state-of-the-art computers can be prohibitive for many workplaces, especially if there is only an occasional need for HPC.

Editors and Affiliations

  • Computer Science Department, University of Tennessee, Knoxville, USA

    Jack Dongarra

  • Department of Informatics and Mathematical Modelling, Technical University of Denmark, Lyngby, Denmark

    Kaj Madsen

  • Informatics & Mathematical Modeling, Technical University of Denmark, Lyngby, Denmark

    Jerzy Waśniewski

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